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Structured prior distributions for the covariance matrix in latent factor models (2024)
Journal Article
Heaps, S. E., & Jermyn, I. H. (2024). Structured prior distributions for the covariance matrix in latent factor models. Statistics and Computing, 34(4), Article 143. https://doi.org/10.1007/s11222-024-10454-0

Factor models are widely used for dimension reduction in the analysis of multivariate data. This is achieved through decomposition of a p×p covariance matrix into the sum of two components. Through a latent factor representation, they can be interpre... Read More about Structured prior distributions for the covariance matrix in latent factor models.

A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis (2022)
Journal Article
Botsas, T., Cumming, J., & Jermyn, I. (2022). A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis. Journal of the Royal Statistical Society: Series C, 71(4), 951-968. https://doi.org/10.1111/rssc.12562

In petroleum well test analysis, deconvolution is used to obtain information about the reservoir system. This information is contained in the response function, which can be estimated by solving an inverse problem in the pressure and flow rate measur... Read More about A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis.

Modality-Constrained Density Estimation via Deformable Templates (2021)
Journal Article
Dasgupta, S., Pati, D., Jermyn, I. H., & Srivastava, A. (2021). Modality-Constrained Density Estimation via Deformable Templates. Technometrics, 63(4), 536-547. https://doi.org/10.1080/00401706.2020.1867647

Estimation of a probability density function (pdf) from its samples, while satisfying certain shape constraints, is an important problem that lacks coverage in the literature. This article introduces a novel geometric, deformable template constrained... Read More about Modality-Constrained Density Estimation via Deformable Templates.

Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach (2020)
Presentation / Conference Contribution
Cumming, J., Botsas, T., Jermyn, I., & Gringarten, A. (2020, December). Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach. Presented at SPE Virtual Europec 2020

Objectives/Scope: A stable, single-well deconvolution algorithm has been introduced for well test analysis in the early 2000’s, that allows to obtain information about the reservoir system not always available from individual flow periods, for exampl... Read More about Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach.

Versatile method for quantifying and analyzing morphological differences in experimentally obtained images (2019)
Journal Article
Bagdassarian, K., Connor, K., Jermyn, I., & Etchells, J. (2020). Versatile method for quantifying and analyzing morphological differences in experimentally obtained images. Plant Signaling & Behavior, 15(1), Article 1693092. https://doi.org/10.1080/15592324.2019.1693092

Analyzing high-resolution images to gain insight into anatomical properties is an essential tool for investigation in many scientific fields. In plant biology, studying plant phenotypes from micrographs is often used to build hypotheses on gene funct... Read More about Versatile method for quantifying and analyzing morphological differences in experimentally obtained images.

Statistical Characterisation of Fluvial Sand Bodies: Implications for Complex Reservoir Models (2019)
Presentation / Conference Contribution
Franzel, M., Jones, S., Jermyn, I., Allen, M., & McCaffrey, K. (2019, December). Statistical Characterisation of Fluvial Sand Bodies: Implications for Complex Reservoir Models. Presented at Petroleum Geostatistics 2019

The three-dimensional geometry of fluvial channel sand bodies has received considerably less attention than their internal sedimentology, despite the importance of sandstone body geometry for subsurface reservoir modelling. The aspect ratio (width/th... Read More about Statistical Characterisation of Fluvial Sand Bodies: Implications for Complex Reservoir Models.

Organ-specific genetic interactions between paralogues of the PXY and ER receptor kinases enforce radial patterning in Arabidopsis vascular tissue (2019)
Journal Article
Wang, N., Bagdassarian, K., Doherty, R., Kroon, J., Connor, K., Wang, X., Wang, W., Jermyn, I., Turner, S., & Etchells, J. (2019). Organ-specific genetic interactions between paralogues of the PXY and ER receptor kinases enforce radial patterning in Arabidopsis vascular tissue. Development, 146(10), Article 177105. https://doi.org/10.1242/dev.177105

In plants, cells do not migrate. Tissues are frequently arranged in concentric rings, thus expansion of inner layers is coordinated with cell division and/or expansion of cells in outer layers. In Arabidopsis stems, receptor kinases, PXY and ER, gene... Read More about Organ-specific genetic interactions between paralogues of the PXY and ER receptor kinases enforce radial patterning in Arabidopsis vascular tissue.

Shape-constrained and unconstrained density estimation using geometric exploration (2018)
Presentation / Conference Contribution
Dasgupta, S., Pati, D., Jermyn, I. H., & Srivastava, A. (2018, June). Shape-constrained and unconstrained density estimation using geometric exploration. Presented at IEEE Statistical Signal Processing Workshop (SSP)., Freiburg, Germany

The problem of nonparametrically estimating probability density functions (pdfs) from observed data requires posing and solving optimization problems on the space of pdfs. We take a geometric approach and explore this space for optimization using act... Read More about Shape-constrained and unconstrained density estimation using geometric exploration.

Paralogues of the PXY and ER receptor kinases enforce radial patterning in plant vascular tissue (2018)
Journal Article
Wang, N., Bagdassarian, K. S., Doherty, R. E., Wang, X. Y., Kroon, J. T., Wang, W., Jermyn, I. H., Turner, S. R., & Etchells, J. P. Paralogues of the PXY and ER receptor kinases enforce radial patterning in plant vascular tissue. https://doi.org/10.1101/357244. Manuscript submitted for publication

Plant cell walls do not allow cells to migrate, thus plant growth and development is entirely the consequence of changes to cell division and cell elongation. Where tissues are arranged in concentric rings, expansion of inner tissue, such as that whi... Read More about Paralogues of the PXY and ER receptor kinases enforce radial patterning in plant vascular tissue.

Elastic 3D shape analysis using square-root normal field representation (2017)
Presentation / Conference Contribution
Laga, H., Jermyn, I. H., Kurtek, S., & Srivastava, A. (2017, December). Elastic 3D shape analysis using square-root normal field representation. Presented at 56th IEEE Conference on Decision and Control., Melbourne, Australia

Shape is an important physical property of natural and man-made 3D objects that characterizes their external appearances. Understanding differences between shapes, and modeling the variability within and across shape classes, hereinafter referred to... Read More about Elastic 3D shape analysis using square-root normal field representation.

Numerical Inversion of SRNF Maps for Elastic Shape Analysis of Genus-Zero Surfaces (2017)
Journal Article
Laga, H., Xie, Q., Jermyn, I. H., & Srivastava, A. (2017). Numerical Inversion of SRNF Maps for Elastic Shape Analysis of Genus-Zero Surfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2451-2464. https://doi.org/10.1109/tpami.2016.2647596

Recent developments in elastic shape analysis (ESA) are motivated by the fact that it provides a comprehensive framework for simultaneous registration, deformation, and comparison of shapes. These methods achieve computational efficiency using certai... Read More about Numerical Inversion of SRNF Maps for Elastic Shape Analysis of Genus-Zero Surfaces.

Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours (2016)
Journal Article
Molnar, C., Jermyn, I. H., Kato, Z., Rahkama, V., Östling, P., Mikkonen, P., …Horvath, P. (2016). Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours. Scientific Reports, 6, Article 32412. https://doi.org/10.1038/srep32412

The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phe... Read More about Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours.

Elastic shape analysis of surfaces and images (2016)
Book Chapter
Kurtek, S., Jermyn, I., Xie, Q., & Klassen, E. (2016). Elastic shape analysis of surfaces and images. In P. K. Turaga, & A. Srivastava (Eds.), Riemannian computing and statistical inferences in computer vision (257-277). Springer Verlag. https://doi.org/10.1007/978-3-319-22957-7_12

We describe two Riemannian frameworks for statistical shape analysis of parameterized surfaces. These methods provide tools for registration, comparison, deformation, averaging, statistical modeling, and random sampling of surface shapes. A crucial p... Read More about Elastic shape analysis of surfaces and images.

Numerical inversion of SRNFs for efficient elastic shape analysis of star-shaped objects (2014)
Presentation / Conference Contribution
Xie, Q., Jermyn, I., Kurtek, S., & Srivastava, A. (2014, September). Numerical inversion of SRNFs for efficient elastic shape analysis of star-shaped objects. Presented at Proc. European Conference on Computer Vision (ECCV), Zurich

The elastic shape analysis of surfaces has proven useful in several application areas, including medical image analysis, vision, and graphics. This approach is based on defining new mathematical representations of parameterized surfaces, including th... Read More about Numerical inversion of SRNFs for efficient elastic shape analysis of star-shaped objects.

Shape as an emergent property (2013)
Book Chapter
Jermyn, I. H. (2013). Shape as an emergent property. In S. Dickinson, & Z. Pizlo (Eds.), Shape perception in human and computer vision : an interdisciplinary perspective (187-199). Springer Verlag. https://doi.org/10.1007/978-1-4471-5195-1_13

Shape is a ubiquitous property of our world. Inferences about it require ‘shape models’: probability distributions on shapes. The crucial property of any such shape model is the existence of long-range dependencies between boundary points. We look at... Read More about Shape as an emergent property.

A multi-layer phase field model for extracting multiple near-circular objects (2012)
Presentation / Conference Contribution
Molnar, C., Kato, Z., & Jermyn, I. (2012, November). A multi-layer phase field model for extracting multiple near-circular objects. Presented at 21st International Conference on Pattern Recognition (ICPR2012)., Tsukuba, Japan

This paper proposes a functional that assigns low `energy' to sets of subsets of the image domain consisting of a number of possibly overlapping near-circular regions of approximately a given radius: a `gas of circles'. The model can be used as a pri... Read More about A multi-layer phase field model for extracting multiple near-circular objects.

Elastic shape matching of parameterized surfaces using square root normal fields (2012)
Presentation / Conference Contribution
Jermyn, I. H., Kurtek, S., Klassen, E., & Srivastava, A. (2012, October). Elastic shape matching of parameterized surfaces using square root normal fields. Presented at 12th European Conference on Computer Vision (ECCV), Florence, Italy

In this paper we define a new methodology for shape analysis of parameterized surfaces, where the main issues are: (1) choice of metric for shape comparisons and (2) invariance to reparameterization. We begin by defining a general elastic metric on t... Read More about Elastic shape matching of parameterized surfaces using square root normal fields.

A phase field method for tomographic reconstruction from limited data (2012)
Presentation / Conference Contribution
Hewett, R. J., Jermyn, I., Heath, M. T., & Kamalabadi, F. (2012, September). A phase field method for tomographic reconstruction from limited data. Presented at British Machine Vision Conference 2012 (BMVC), Guildford, Surrey

Classical tomographic reconstruction methods fail for problems in which there is extreme temporal and spatial sparsity in the measured data. Reconstruction of coronal mass ejections (CMEs), a space weather phenomenon with potential negative effects o... Read More about A phase field method for tomographic reconstruction from limited data.